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Research Article
Open Access Peer-reviewed

Rural Development Planning – A Case Study in Developing Geospatial Data Infrastructure with the help of GIS, Remote Sensing and GPS

Nebare Poi, Tingneyuc Sekac, Sujoy Kumar Jana , Dilip Kumar Pal
American Journal of Rural Development. 2018, 6(3), 59-70. DOI: 10.12691/ajrd-6-3-1
Received August 03, 2018; Revised September 13, 2018; Accepted September 28, 2018

Abstract

Papua New Guinea (PNG) government has introduced the decentralised governance with the plan to improve service delivery and also to strengthen the implementation capacity of local administration. In order to realise this goal it is necessary for the local administration to be sourced with reliable baseline data to service the needs of district development authority (DDA) and sister planning organisations. Decision on the subject of appropriate locations and targeting the right people, monitoring activities, assessing constraints and mobilising resources for rural development demand computer-based geographically connected database, incorporating charts, maps and statistical reports to service the needs of planners and decision makers. The current research focuses on utilising geospatial technologies such as Remote Sensing, GIS and GPS to develop and analyse spatial data infrastructure in particular roads, bridges, health facilities and schools based on their conditions, availability, accessibility to the community and affordability at the local level Governments (LLGs) of Salt Nomane Karimui District, Simbu province of Papua New Guinea. Village based geospatial database is created by integrating spatial and non-spatial database under GIS environment for decentralised planning at local administration. The results emanating from this analysis will serve as District information tool to help improve planning, design and delivery of initiatives, particularly to address the needs of underprivileged groups and individuals at village level. The results were made public as a means of transparency in information communication for unbiased, scientific decision-making and efficient planning to achieve development objectives at the local administration level. A computer-based GIS database was generated at a micro administrative unit as output for decentralised planning and decision-making at the local administration.

1. Introduction

At present the government of Papua New Guinea (PNG) is in the midst of a major reform of its organic laws. One of the major transformations in 2013 was Decentralised Governance with the plan to improve service delivery and strengthen the implementation capacity of local administration. This has guided the government to establish District Development Authorities (DDAs) with the aim of implementing the directives of national government. From that time onwards the national Government has been pivotal in empowering Members of Parliament (MPs) with more control and discretion to deliver development projects at the District level. However, the local authorities have encountered a lot of difficulties in implementing rural development programmes in PNG. However, there is a hitch here in the form of unavailability of a decision support system (DSS) based on a reliable spatial data infrastructure to be created with the state of the art geospatial technologies. There are so many cases in PNG reported in recent times that the development programmes in rural areas have not been delivered up to expectations and /or have never been implemented by authorities as pointed out by Care International in Papua New Guinea (CIPNG) and Community Development Agency (CDA) in their joint baseline survey in Rural districts of Simbu in 2013. In combating such complex challenges, Geospatial technologies such as GPS, GIS and Remote Sensing are such technological tools that allow us to develop a spatial data infrastructure of any geographical area, which is very important in planning, monitoring and decision-making at any levels of administration.

As it was summarised by Adinarayana et. al. 1, GIS and the underlying Spatial Data Infrastructures have the potential to assist in planning, monitoring and exchange of information between various agencies in rural development administration. Any development programmes to be implemented by a local administration need a lot of baseline data with planning tool to identify priority areas and target people, allocation of funds, monitoring activities, assessing results, assessing the constraints, mobilising resources, etc., as pointed out by Yadav and Singh 2. It is extensively recognized that Geospatial technology at micro level plays a key role in disseminating information at local level for promoting and monitoring balanced development across rural areas. A study carried out by Yadav and Singh 3 affirmed that Geospatial technology is being used to improve planning, design and delivery of initiatives, particularly to address the needs of underprivileged groups and individuals at village level. It is further stated that, GIS-based systems have been developed for mapping of infrastructure, which is very helpful in identifying the gaps in availability of basic amenities and locations where facilities are necessary to be provided.

All the village information are spatially integrated and form part of common coordinate system in a GIS environment, planners can quickly get a broader view of current situation at the village level and more accurately assess future implications. Geospatial technology plays a fundamental role in generating timely and reliable information for planning and decision making at all levels from macro to micro for a region 4, 5. Salt Nomane Karimui District in Simbu Province is one of those least developed districts in the country that continue to face enormous development challenges in planning and delivering development projects. Hence, a decision in regards to planning in the right location and target people require a sophisticated computer based geographically connected database to service the needs of planners and decision makers. As such geospatial technologies are capable of generating timely and reliable information to service the needs of planning organisation. The local administrative system can be modernized and accelerated through Geospatial technology for informed decision-making and planning to ensure balanced development across the unprivileged and disadvantaged group of villages.

This study intends to create geographically connected geospatial database at village level as a micro administrative unit. The particular emphasis is on identifying and mapping road networks, bridges, health facilities and education facilities in each LLGS of Salt Nomane Karimui district taking into consideration the distribution, conditions, availability, accessibility and affordability of each infrastructural facility. The output produced will form basis of micro administrative plans and management schemes to identify local needs and limitations of a ward as workable micro-administrative unit. The planners and decision makers would make use of this computer-based GIS system to chart out the progress of citizen participation and community input so as to develop a vision for the community which then enhances the quality of life for all the citizens.

1.1. Study Area Background Information

This research was carried out in the tribal oriented and rural based Salt, Nomane and Karimui LLGs of SNK district in Simbu Province, PNG (Figure 1). Salt Nomane Karimui is one of the most remote districts in Simbu province and one of the top 5 least developed districts in the country. It comprises of three LLGs namely Salt, Nomane and Karimui. Salt LLG is approximately 25 km South of Kundiawa, Simbu provincial head quarter while other two are 35km and 55 km respectively further south of Kundiawa. Salt Nomane Karimui District is situated in a mixture of mountainous and rugged terrain at the northern part while roughly 75 percent of the entire landmass is plain and very rich in natural fertile volcanic soil. It also contains beautiful and un-exploited natural habitat within its forests. It covers a land mass of about 35086 ha and has a total population of 52159 excluding children below eighteen years of age as record by the national census of PNG, 2011.

It hosts one of the highest mountains in the province, Mt crater and number of smaller mountain ranges in the Province which are known for the home of some unique and rare species of flora and creatures within its natural forest. It also hosts one of the biggest rivers (Wahgi) in the highlands region of PNG and number of fast flowing rivers and streams. It is the biggest district occupying over half of the geographical expanse of Simbu province.

As regards the socio economic condition of the region (SNK) almost 95 percent of population practise subsistence farming where people cultivate land for food and shelter. This has been the source of survival for years, and will continue to be the same in the foreseeable future. It is important to note that about 80% of its landmass is capable of producing very good yield for large scale economical crops due to its natural fertility of the amiable landscape. As a result, the potential of economic activities in this region is relatively high compared to other districts in Simbu province, but remains untapped unfortunately.

2. Data and Study Approach

The methodology is pivoted around developing a geospatial database to integrate both spatial and non-spatial data under a GIS environment. It involves the generation of village ward maps, linking of non-spatial data to corresponding spatial entity using GIS, integration of spatial and non-spatial databases through the use of common identifiers, and finally the generation of views and scenarios for planning and decision-making. The flowchart in Figure 2 illustrates the methodology carried out for data evaluation, analysis and results preparation.

2.1. Data Collection and Pre-processing

The underlying principle of analysis, the collection of both spatial and non-spatial data was essential. The spatial data collected was mostly field data captured using GPS (GPS data) and existing PNGRIS and Geobook data collected from Department of Surveying and land study, PNG University of technology. The data collected through GPS was organised in Excel spreadsheet with its attribute and X, Y information. These are position coordinates of the targeted infrastructure facilities, tracks and line segments of road networks in the study area. The X, Y data were temporarily displayed in data frame and saved as feature classes or shape files for retrieval and analysis. The data was further verified and updated through field visit and also through assistance of high resolution Google earth imagery. The attribute database created in the Excel spreadsheet with reference to each geographical X, Y point is automatically generated in ArcGIS for each positional feature. The non-spatial (Attribute) data were collected through questionnaires, interviews, field visits and physical visits to government’s and NGOs’ offices in Simbu province. The non spatial data including demographic and socio-economic data, as well as built-up infrastructures data were spatially organised in a common coordinate system and later on integrated with collected spatial data with SRTM 30m spatial resolution Elevation data and PALSAR L-Band, 50m resolution Mosaic data in the GIS environment. The Spatial data were normally stockpiled as coordinates and topology (attributes). Any form of dataset is not readily related to a location on the earth surface, it is referred to as non-spatial data. Examples of non-spatial data were numbers, characters or logical expressions and were later connected to spatial data to provide more locational information. The data collected were population data and built-up infrastructures data, such as data on roads, bridges, health centres, post offices and schools. Additionally the village position data was also collected. The infrastructures data collected were assessed by way of considering their conditions, status, distribution, community accessibility and affordability. Figure 3, Figure 4 and Figure 5 illustrates some key data collected and were used for analysis and assessment in GIS environment.

2.2. Data Analysis

The integrated Geospatial data were mapped as illustrated in Figure 3, Figure 4 A and B. These datasets were evaluated and analysed in such a way as to put out information for decision makers and planners to serve the growing population of the study region as illustrated in Figure 5. As hinted earlier, the infrastructures were analysed in terms of their conditions, distributions and accessibility based on the perceptions of surrounding villages and the growing population (Figure 5). The primary spatial analyses techniques bring into play were overlay, feature digitizing and multiple ring buffer method. These GIS technical approaches adopted were according to the nature of field data collected. Hence distribution and condition of infrastructure were mapped and the database was created accordingly. From the Initial existing spatial data collected as highlighted above, the infrastructure information was digitized and extracted. Non-spatial data collected by way of field visits was performed analysis according to their conditions, distributions and connectivity, whilst maps were prepared leading to generation of the geospatial database system.

In addition all the village positions were digitized and extracted, attributing to the population allocation of each village. The overlay approach in the ArcGIS environment was carried out to discover and appraise all digitized features based on the distributions when compared with nearby villages or populations in terms of accessibility and efficient service provision concept. The overlay method is a GIS operation that combines the geometrics and attributes of the input layer (created digitized layer) to create the output layer. The multiple ring buffer technique was then performed after making all the comparisons and judgments through an understanding of overlay technique that provides visualization of interrelationship of each built-up infrastructure and the close by surviving population within the three (3) LLGs of study region.

Buffering is a GIS function that generates zones within the defined distance of selected features. For instance, a school might be buffered by two km radius and then we may use the buffer to select students resides beyond two km to plan for their pick up and drop off transportations. The creation of buffer zones for each infrastructure was selected in accordance with the specified distance in kilometre. The school and health infrastructures were digitized in point format and they are identified as sources while growing population in each villages are pointed out as targets to benefit from these sources. Hence, the point feature buffering was performed to point out and illustrate the distance in which each village or population is away from the source features. However, it is also important to show unbearable obstacle and/or accessibility limiting factors within the buffer such as terrain height or river to cross over to the service sites (source). The buffering was also performed for road network to display and identify ease or difficulty of certain villages accessing road. These are necessary analyses performed for such a database. The purpose of the study is to show the degree of difficulty or ease of access and the availability of government services that are benefited by the growing population within the study region.

3. Results and Discussion

3.1. Introduction

Easy access to basic health care, education, road and other public amenities for people living and working in rural areas is a key issue within PNG. In this study the government built infrastructure within the study region is regarded as ‘source’ while village populations in each ward are considered as target beneficiaries. The main focuses of discussion are accessibilities, availabilities and current conditions of infrastructural facilities within the study region.

3.2. Road Infrastructure

A developing country like PNG with majority living in rural settings, road transport plays a very important role in determining the level of user satisfaction with any developments. A good road connection in rural settlements provides better access to markets and other public amenities. The poor state of the road connectivity combined with undependable transportation services has an adverse impact on accessibility to markets and public amenities. Better road transportation serves as one of the channels for the collection and exchange of goods and services, unhindered movement of people, dissemination of information and the promotion of rural economy 6. The road network of SNK districts in this study is mapped and classified based on the roads’ condition and usage. The study is based on four areas namely: distance access by village wards, accessibility considering terrain factor, the general condition of the road and distribution of roads in each LLG area. The majority of rural villages are isolated by distance, physical geography, bad road conditions, lack of or broken bridges and inadequate transportation. These conditions make it difficult for people to get their goods to market and/or access public amenities.

The districts’ road is the only serviceable road linking habitants as no other village road links are in operation. Hence, those village wards living within 0 to 3 km are having easy access while wards further away from 3 km are continuously confronted with challenges due to difficult terrain. Those living within 7km to 15km and beyond are considered as disadvantaged groups of villagers. They continue to miss out on this service as well as other public amenities. Figure 6 illustrates the overall assessment of road distribution in SNK in percentages and Figure 7 shows village locations and accessibility to existing road infrastructure. The most disadvantaged villages are likely to be those that are relatively isolated and have limited access to road infrastructure.

Difficult Terrain is one of the factors that limit the accessibility of road and other public utilities within the region. When comparing the road network in Figure 3 and road buffer with the levels of altitude/elevation as illustrated in Figure 7 A and 7B, it can be seen that some villages located on higher terrain areas do face difficulties accessing roads. Hence those villages located in low altitudes in which the public utilities are provided, including roads, are having easy access even several kilometres away from the service. Those villages that are located close to public services but within a difficult terrain emanate challenges while those located in low attitudes have stress-free access in a reduced amount of time.


3.2.1. Road Condition

The condition of the road is one of the contributing factors that hold back the progress of economic activities as well as the accessibility to public utilities. From this study it shows that, only the main section of the road network covering Salt LLG (Figure 3) is in good condition as illustrated in (Figure 8). The other sections of the road links are in very bad and deteriorating conditions. However Karimui LLG is completely cut off by road network. As a result, more than half of the villages in SNK district are disconnected from other basic services. This is a real cause of concern to the district in the future as good road link is the economic life line and the only access to other services. The road is classified based on its current condition and usage. Fair roads are defined as village access roads with improper drainage system and rough surface but frequently used by habitants. Bad roads are defined as very terrible stage of deteriorating and in a dreadful condition which are not up to usable standards but frequently used by habitants. The entire roads linking SNK District are unmanageable and their accessibility is limited. Access to walking track in this category refers to villages without any road links. Their access is through bush tracks as illustrated in Figure 8. From this study it shows that the entire population of Karimui LLG is having access to bush tracks only but often find it tough to walk due to difficult terrain and the insufferable walking distance. The entire villages in Karimui LLG are completely disconnected from road network and encounter greater difficulties in accessing basic services such as health, education, electricity, markets, shopping centres and the list goes on. They must do so with other forms of transportation to satisfy immediate needs and that is air transport. But investment in air transportation is extremely expensive, also considering the socioeconomic scenario the sustenance is ruled out even if the initial investment is made. Consequently, the dispersed population living in this part of the region continues to face enormous development challenges. If nothing is done to improve the road network, they will continue to face the real challenge in the foreseeable future.

3.3. Health Infrastructure

Basic health service is one of the essential social services sustaining humans in numerous ways. The Government of PNG is resolute to reach out to rural areas by providing primary and essential health care for everyone with the free health care policy. As such this study intends to assess the availability of basic health services in the study area as well as their condition and the distance in which health service is accessed by local communities. The distribution of existing health facilities in three LLGs of SNK district is presented in Figure 9. The computation is based on the total number of health facilities provided in each LLGs of SNK district. Two Health centres are provided at sub District administrative unit as shown in Figure 4 B. One sub-health Centre is provided at Nomane LLG administrative unit and two in Karimui LLG. However, this study shows that the distribution of health services taking into account of aid posts across the district are not adequately available in each LLG as per the LLG wards.

A good health service in rural settings is considered as one of the most important community basic social services. Basic Healthcare is captured in the top priority list of government’s investment. However, the spatial map of health services available in the study area (Figure 10A) shows that, more than half of the population are not having easy access to existing facilities. The fortunate groups that have easy access to existing public health services are those within 3km zone. Those villages located between 3km to 5km continue to come across so many challenges while those living beyond are considered as most disadvantaged and unprivileged group. The possibility of having access to existing facilities is very limited due to difficult topography and the distance in which this service is made available. The terrain analysis also provides additional information on the accessibilities as illustrated on Figure 10 B.

The nature of dificult terrain and location at which this service is provided, some villages are regarded as fortunate while others are not due to difficult terrain. Whilst comparing the road network and road buffer as illustrated in Figure 7 A, B and terrain map in Figure 10 B with the levels of altitude/elevation of the study area, it can be seen that some villages are located on difficult terrain areas and do face difficulties accessing health services. Hence, those villages located at very low to low attitude are having easy access through a walk while those located in high attitude are not so lucky due to difficult terrain. The sad state of affairs is that, those villages within close distance but are located at high to very high altitude are so severely challenged to access. It takes awful walking hours to reach the destination, which is extremely cumbersome; while those situated at very low to low altitudes are having trouble- free access even though they are far away from the service utilities.


3.3.1. Condition of Health Facilities

The available health facilities in the district are evaluated and classified based on current condition, including state of staff housing, state of clinic facilities, availability of trained medical staff, availability of medicine and the capacity in which health services are able to perform. The map in Figure 11 shows the location of operating health clinics. The bad condition refers to rundown health facilities which are not operational. The fair condition refers to very deteriorating and rundown health facilities in which services are still being provided. Good condition refers to health facilities which require immediate maintenance but are functioning well with adequate supply of medicine and staff. According to this study it shows that there is no medical centre in very good condition as per the assessment which means that there is no good infrastructure and utilities as well as adequate manpower and medicine supplies with effective clinical operations in the study region. Also this study shows that, most of the aid posts in the villages are not functioning while others are in dire need of renovation.

3.4. Education Facilities

Education is regarded as one of the priority areas of investment of the current government. However, based on spatial maps (Figure 4 A and Figure 13 B), almost all wards have elementary schools as the mandatory requirement of the local administration which is not included as it is adequately provided but there is a need for more primary schools and secondary schools. Also some of the current conditions of education facilities provided in the three LLGs are in very bad state of maintenance as identified in this study. The total number of schools in each LLG is provided in Figure 12. This distribution is a summary report of all the levels of education facilities available from primary to high schools. The study result shows that secondary and technical or vocational schools are not provided in the district and it’s a real case of poor situation where the authorities seriously need to look in to it. However primary and high schools are not sufficiently provided. From this study it shows that there are many Villages in each LLG not having easy access to Education. The availability of primary school, the distance from surrounding village and the stage of facilities are of paramount concern as to accommodate the increased number of kids coming out from each village. When compared with the map in Figure 13 A and B, it indicates that those kids graduating from elementary schools in each village wards are having difficulty in accessing nearby primary schools as villages are scattered. Those villages’ wards within 0 to 2 km are having easy access while those within 2 to 5 kilometres are struggling due to distance and difficult terrain. However, village wards further away from 5 km are considered as disadvantaged and unprivileged group as kids cannot walk that far. As such there is a high chance of kids missing out on basic education. Also there are two high schools in the study areas (Figure 14). It indicates that the conditions are up to the expected standard. The distances within these services do not affect the users as the schools provide boarding facilities to accommodate students. However, there is a need for additional high schools to cater for increased number of enrolments and a secondary school to accommodate students from high schools as it requires instant consideration. Also from the map in Figure 13, A and B, it can be concluded that the village wards away from school beyond 5km are more than enough to justify additional high schools and it is contended that government needs to make this dream possible.

There is good number of primary schools provided in three LLGs of SNK District to cater for the increased number of kids. All the primary schools are programmed in such a way to accommodate both upper and lower primary levels. Their enrolment comes from elementary school. This comes to the core of struggles identified from this study as almost all of the elementary graduates are unable to access nearby primary schools due to distance and difficult topography. When comparing the elevation/altitude level in Figure 13 B with Figure 4, A, those villages situated within 0 to 2km buffer distance and in very low altitude have easy access, while 2 to 5 km come across much challenges. However, villages located in the low altitude from 2 to 5 km away from school still have easy commutes, while in the high altitude it is hard to hike the terrain to reach the destination. As a result, few kids continue to lower primary while a lot of them are left behind excluded in the villages.


3.4.1. Condition of Education Facilities

The condition of available education facilities shown (Figure 15) is classified based on the current state of staff houses classrooms, and their utilities (Learning material). Bad condition refers to wooden materials, which require immediate maintenance and/or rundown schools which are not in operation due to lack of maintenance, facilities and utilities. Fair condition refers to schools with semipermanent buildings, which require major maintenance as well as utilities that are not up to standards but are nevertheless in operation. Good condition refers to schools with both permanent and semi-permanent buildings and well established amenities like toilets and rubbish disposal, learning materials, etc., with effective operations. Very good is classified based on its current condition, which requires minor maintenance; utilities and learning materials are well maintained and the general operational functions with regards to enrolment and availability of skilled staff are up to expectation. From this study it shows that more than half of the schools require immediate maintenance to improve the standard of learning to the anticipated level.

4. Conclusion and Recommendation

This study is carried out in Salt Nomane Karimui the remotest district of Simbu Province in PNG, to generate Geospatial data infrastructure with main emphasis on mapping basic rural infrastructure including road network, health facilities and education facilities for development planning in the district. The main focus is on demonstrating the potential of spatial data infrastructure at local administrative unit for future development planning, taking into consideration the local needs and constraints. This study provides useful information in the form of maps, charts and statistical reports to support decision-makers in the district to generate views on community participation towards decision-making at the district level. The output result is much like a prototype district administrative GIS tool designed to serve as a first step towards any development of Advanced Geospatial Database for decentralized planning at local administration. The geospatial database developed is modular and can be updated in the future to accommodate additional information about the district through new thematic layers to make it more comprehensive.

PNG geography and the socioeconomic conditions of its Citizens, makes it a challenge for the Government of PNG to access current up to date and reliable data to assist in their decision-making process for rural development planning. Hence a systematic planning and management system is a paramount necessity for PNG government to drive its development objectives. Geospatial technologies such as GPS, GIS and Remote Sensing systems have the potential to support decision-makers, planners and environmental managers’ in so many ways in planning better service delivery and management practices. Most likely future geospatial development programmes to be incorporated from this study include; Graphical User Interface (GUI) could be built from this database. It is a menu driven user friendly system, provide quality and up to date information for non –GIS professionals. It is indeed a very fast, friendly and convenient tool for user community, strategic Unit for Decentralized planning: Given that all village informatics are now spatially part of a common coordinated system, a number of useful combinations can be performed. The first step in this process is to create Integrated Resource Unit (IRU). Each IRU comprises the spatial and non-spatial resource data, and can be taken as a strategic unit for assessing various decisions. Since they exhibit strong uniformity, they can all be expected to respond similarly to given intensities of human use and management strategies, advanced and sophisticated computer based Decision Support Systems (DSS) could also surface from this Geospatial database. The availability of geographically connected database of various data sources organised in a computer system is more important as data security is concerned. The integrated database created from this study can be customised in GIS- based Computer system to develop a Decision Support System for the District to use as a tool in planning and managing rural development programs. Recommendations for further execution of other GIS system will be assessed from time to time when this system is in full operation and also recommendation for further development on Geospatial database will be developed from this prototype Village based information system.

References

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[2]  Yadav, L. R. and Sing, R. S. (2009), GIS Applications in Statistical System and Micro Level Planning Strengthening, 10th ESRI India User Conference 2009.
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[3]  Yadav, L. R. and Sing, R. S. (2011), Strengthening local level planning in Uttar Pradesh, geo-spatial today; Available Online at: http://emanchitra.up.nic.in/emanchitra/articles/Planning_Development.pdf; accessed on 10-12-2016.
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[4]  Gupta, R. D. (2007), Geostatistical Modelling for Assessment of Development at Micro Level, Presented in ASPRS International Spring Conference on Identifying Geospatial Solutions, May 7-11, 2007, Tampa, Florida, USA
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[5]  Bariar, A., Gupta, R. D., Prasad, S. C., (2007), Development of GIS based Spatial Data Infrastructure for Micro-Level Planning, International Conference: Map World Forum, 22-25 January, Hyderabad, India.
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[7]  Bryan, J.E. and Sherman, P.L. (2008). Papua New Guinea Resource Information Handbook 3rd. Ed., University of Papua New Guinea.
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[8]  Majumdar K. L., and Sinha R. L. P. (1992), “A GIS based Information System for Regional Planning – A Case Study for Bharatpur District” Govt. of India, SAC, Ahmedabad, TCPO, New Delhi.
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[9]  Wiltshire, C. and Opermann, T. (2015), Politicising Drought relief in PNG, State, Society & Governance in Melanesia, Australian National University, Available Online at: http://ssgm.bellschool.anu.edu.au/sites/default/files/publications/attachments/201607/ib2015.66_wiltshire_ and_oppermann.pdf; accessed on 07-12-2016.
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Published with license by Science and Education Publishing, Copyright © 2018 Nebare Poi, Tingneyuc Sekac, Sujoy Kumar Jana and Dilip Kumar Pal

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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Nebare Poi, Tingneyuc Sekac, Sujoy Kumar Jana, Dilip Kumar Pal. Rural Development Planning – A Case Study in Developing Geospatial Data Infrastructure with the help of GIS, Remote Sensing and GPS. American Journal of Rural Development. Vol. 6, No. 3, 2018, pp 59-70. http://pubs.sciepub.com/ajrd/6/3/1
MLA Style
Poi, Nebare, et al. "Rural Development Planning – A Case Study in Developing Geospatial Data Infrastructure with the help of GIS, Remote Sensing and GPS." American Journal of Rural Development 6.3 (2018): 59-70.
APA Style
Poi, N. , Sekac, T. , Jana, S. K. , & Pal, D. K. (2018). Rural Development Planning – A Case Study in Developing Geospatial Data Infrastructure with the help of GIS, Remote Sensing and GPS. American Journal of Rural Development, 6(3), 59-70.
Chicago Style
Poi, Nebare, Tingneyuc Sekac, Sujoy Kumar Jana, and Dilip Kumar Pal. "Rural Development Planning – A Case Study in Developing Geospatial Data Infrastructure with the help of GIS, Remote Sensing and GPS." American Journal of Rural Development 6, no. 3 (2018): 59-70.
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[1]  Adinarayana, J., Raj, F. J., and Sharma, V. (2004). Village level information system – a tool for decentralized planning at district level in India, International Journal of Environmental Informatics, 4(2): 56-64.
In article      View Article
 
[2]  Yadav, L. R. and Sing, R. S. (2009), GIS Applications in Statistical System and Micro Level Planning Strengthening, 10th ESRI India User Conference 2009.
In article      
 
[3]  Yadav, L. R. and Sing, R. S. (2011), Strengthening local level planning in Uttar Pradesh, geo-spatial today; Available Online at: http://emanchitra.up.nic.in/emanchitra/articles/Planning_Development.pdf; accessed on 10-12-2016.
In article      View Article
 
[4]  Gupta, R. D. (2007), Geostatistical Modelling for Assessment of Development at Micro Level, Presented in ASPRS International Spring Conference on Identifying Geospatial Solutions, May 7-11, 2007, Tampa, Florida, USA
In article      
 
[5]  Bariar, A., Gupta, R. D., Prasad, S. C., (2007), Development of GIS based Spatial Data Infrastructure for Micro-Level Planning, International Conference: Map World Forum, 22-25 January, Hyderabad, India.
In article      
 
[6]  Adedeji, O. A., Olafiaji, E. M., Omole, F. K., Olanibi, J. A., Lukman, Y. (2014): An Assessment of the Impact of Road Transport on Rural Development: A case Study of Obokun Local Government Area of Osun State, Nigeria. British Journal of Environmental Sciences 2(1), 34-48.
In article      
 
[7]  Bryan, J.E. and Sherman, P.L. (2008). Papua New Guinea Resource Information Handbook 3rd. Ed., University of Papua New Guinea.
In article      
 
[8]  Majumdar K. L., and Sinha R. L. P. (1992), “A GIS based Information System for Regional Planning – A Case Study for Bharatpur District” Govt. of India, SAC, Ahmedabad, TCPO, New Delhi.
In article      
 
[9]  Wiltshire, C. and Opermann, T. (2015), Politicising Drought relief in PNG, State, Society & Governance in Melanesia, Australian National University, Available Online at: http://ssgm.bellschool.anu.edu.au/sites/default/files/publications/attachments/201607/ib2015.66_wiltshire_ and_oppermann.pdf; accessed on 07-12-2016.
In article      View Article